Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/330712 
Year of Publication: 
2025
Citation: 
[Journal:] International Entrepreneurship and Management Journal [ISSN:] 1555-1938 [Volume:] 21 [Issue:] 1 [Article No.:] 111 [Publisher:] Springer US [Place:] New York, NY [Year:] 2025
Publisher: 
Springer US, New York, NY
Abstract: 
Supporting academic spinoffs is a vital aspect of innovation and technology policy, as these ventures contribute to economic growth. The early stage – from idea development to company formation – is especially critical due to challenges in securing private financing. Public startup grants, such as the 'EXIST – Business Startup Grant' (EGS) in Germany, aim to bridge this gap. Despite previous evaluations, it remains unclear whether a grant such as the EGS effectively motivates recipients to establish a company formally and engage in economic activity. This study evaluates the effectiveness of the EGS program using register data on the outcome variable and a regression discontinuity design, a robust quasi-experimental research design that utilizes an intervention group and a comparison group to estimate causal program effects. The findings demonstrate that EGS funding at least doubles the likelihood of company formation, depending on model specification, with odds ratios ranging from 4.83 to 10.79. The statistically significant intervention effect remains robust across multiple model specifications, highlighting the program's impact on founding probability by reducing entrepreneurial risks, advancing business planning, and fostering product development. These results suggest that targeted early-stage support can effectively address barriers faced by high-risk academic startups. Policy implications include the importance of integrating financial resources with access to mentoring, coaching, education and institutional networks to enhance startup success. Future research should explore the transferability of these findings to other regional and institutional contexts.
Subjects: 
Academic spinoff
Startup
Startup grant
Startup funding
Regression discontinuity design
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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